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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationSat, 08 Nov 2008 09:06:22 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/08/t1226160418gxaw34kzofcb0ne.htm/, Retrieved Sun, 19 May 2024 09:19:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22615, Retrieved Sun, 19 May 2024 09:19:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Bivariate Kernel Density Estimation] [Various EDA topic...] [2008-11-08 16:06:22] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
Feedback Forum
2008-11-24 18:10:01 [Niels Herremans] [reply
Ook hier weer dezelfde opmerking als bij de eerste en tweede berekening. Hier is er een hoge positieve correlatie. Punten met eenzelfde density worden met elkaar veronden zodat er hoogtelijnen ontstaan. De meeste punten en cluster liggen redelijk dicht bij de rechte. Een rode kleur betekent dat er een hoge density is.

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Dataseries X:
1.00
1.04
1.02
1.07
1.12
1.08
1.02
1.01
1.04
0.98
0.95
0.94
0.94
0.96
0.97
1.03
1.01
0.99
1.00
1.00
1.02
1.01
0.99
0.98
1.01
1.03
1.03
1.00
0.96
0.97
0.98
1.02
1.04
1.01
1.01
1.00
1.01
1.02
1.03
1.06
1.12
1.12
1.13
1.13
1.13
1.17
1.14
1.08
1.07
1.12
1.14
1.21
1.20
1.23
1.29
1.31
1.37
1.35
1.26
1.26
Dataseries Y:
526,4
526,4
526,4
526,4
526,4
526,4
542,9
542,9
542,9
542,9
542,9
542,9
556,11
556,11
556,11
556,11
556,11
556,11
557,07
557,07
557,07
557,07
557,07
557,07
564,29
564,29
564,29
564,29
564,29
564,29
569
569
569
569
569
569
575
575
575
575
575
575
594,51
594,51
594,51
594,51
594,51
594,51
603,88
603,88
603,88
603,88
603,88
603,88
610,02
610,02
610,02
610,02
610,02
610,02




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22615&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22615&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22615&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Bandwidth
x axis0.0263454701398072
y axis7.61090689114796
Correlation
correlation used in KDE0.735846734929663
correlation(x,y)0.735846734929663

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.0263454701398072 \tabularnewline
y axis & 7.61090689114796 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.735846734929663 \tabularnewline
correlation(x,y) & 0.735846734929663 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22615&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.0263454701398072[/C][/ROW]
[ROW][C]y axis[/C][C]7.61090689114796[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.735846734929663[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.735846734929663[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22615&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22615&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Bandwidth
x axis0.0263454701398072
y axis7.61090689114796
Correlation
correlation used in KDE0.735846734929663
correlation(x,y)0.735846734929663



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
if (par3==0) par3 <- dpik(x)
if (par4==0) par4 <- dpik(y)
if (par5==0) par5 <- cor(x,y)
if (par1 > 500) par1 <- 500
if (par2 > 500) par2 <- 500
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par7=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x axis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'y axis',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation used in KDE',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation(x,y)',header=TRUE)
a<-table.element(a,cor(x,y))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')